Evaluating socioeconomic and racial differences in traffic-related metrics in the United States using a GIS approach

Abstract

Previous studies have reported that lower-income and minority populations are more likely to live near major roads. This study quantifies associations between socioeconomic status, racial/ethnic variables, and traffic-related exposure metrics for the United States. Using geographic information systems (GIS), traffic-related exposure metrics were represented by road and traffic densities at the census tract level. Spearman's correlation coefficients estimated relationships between socio-demographic variables and traffic-related exposure metrics, and ANOVA was performed to test for significant differences in socio-demographic variables for census tracts with low and high traffic-related metrics. For all census tracts in the United States, %Whites, %Blacks, and %Hispanics (percent of tract population) had correlation coefficients greater than 0.38 and 0.16 with road density and traffic density, respectively. Regions and states had correlation coefficients as high as 0.78. Compared with tracts with low road and traffic densities (<25th percentile), tracts with high densities (>75th percentile) had values of %Blacks and %Hispanics that were more than twice as high, 20% greater poverty levels, and one-third fewer White residents. Census tracts that had mid-level values for road and traffic densities had the most affluent characteristics. Results suggest that racial/ethnic and socioeconomic disparities exist on national level with respect to lower-income and minority populations living near high traffic and road density areas.